Zhou2016 - BIDS
Authors/Creators
Description
Motor Imagery dataset from Zhou et al 2016.
PapersWithCode leaderboard: https://paperswithcode.com/dataset/zhou2016-moabb
Dataset summary
|
#Subj |
4 |
|
#Chan |
14 |
|
#Classes |
3 |
|
#Trials / class |
160 |
|
Trials length |
5 s |
|
Freq |
250 Hz |
|
#Sessions |
3 |
|
#Runs |
2 |
|
Total_trials |
11496 |
Dataset from the article A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface [1]. This dataset contains data recorded on 4 subjects performing 3 type of motor imagery: left hand, right hand and feet.
Every subject went through three sessions, each of which contained two consecutive runs with several minutes inter-run breaks, and each run comprised 75 trials (25 trials per class). The intervals between two sessions varied from several days to several months.
A trial started by a short beep indicating 1 s preparation time, and followed by a red arrow pointing randomly to three directions (left, right, or bottom) lasting for 5 s and then presented a black screen for 4 s. The subject was instructed to immediately perform the imagination tasks of the left hand, right hand or foot movement respectively according to the cue direction, and try to relax during the black screen.
References
Zhou B, Wu X, Lv Z, Zhang L, Guo X (2016) A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface. PLoS ONE 11(9). https://doi.org/10.1371/journal.pone.0162657
Files
dataset_description.json
Files
(126.3 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:0e45302d8379ae3438e33b11fecb5c61
|
493 Bytes | Preview Download |
|
md5:c585c4afc65d3af43030a4196c31a119
|
756 Bytes | Preview Download |
|
md5:5510f53b0d3ef6c7291992b8d6bc1020
|
149 Bytes | Download |
|
md5:83effba1d88f1ff99185cc6e9a70722b
|
692 Bytes | Download |
|
md5:1df3bd036ed6bc6e0e20b37033d7eeaf
|
39.4 MB | Preview Download |
|
md5:24406af5aa8ddd6597bc4c3d48aea6e7
|
27.2 MB | Preview Download |
|
md5:13384211933d7788af9dbe84802bb980
|
31.0 MB | Preview Download |
|
md5:bd7e5060076c9312e0ed94809aea0d05
|
28.8 MB | Preview Download |
Additional details
Identifiers
Dates
- Accepted
-
2016